{"access":{"advertiser_pricing_url":"https://aidevboard.com/pricing","catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. API keys are optional for stable agent identity and keyed hourly throttling.","docs_url":"https://aidevboard.com/docs","mode":"open","register_url":"https://aidevboard.com/api/v1/register"},"degraded":false,"estimated":false,"has_next":true,"jobs":[{"id":"d5817836-ec6a-4a44-8482-6cb7a1c60532","company_id":"ab3e4567-6f87-4ccf-9ec0-81fd82105f48","title":"Senior Data Scientist, Detection","slug":"senior-data-scientist-detection-6c1be6df","description":"About Us \n \n At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. \n At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a \"normalized\" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in.\n Available Locations- New York\n About the Role \n Cloudflare’s Engineering Team is home to some of the industry’s top engineers, dedicated to building and scaling innovative software that handles a huge proportion of the Internet. Our Detection department sits at the heart of that mission: we identify automated, fraudulent, and malicious activity across the Internet and through our gateway. We develop advanced detection systems and machine learning models that operate at scale, collaborating with Product and Engineering teams across the company to protect our customers and stay ahead of the constantly evolving threat landscape.\n Responsibilities \n \n Research, design, and evaluate detection models that identify automated, fraudulent, and malicious activity across Internet-scale data.\n Dig into massive datasets to uncover the patterns and behaviors that distinguish adversaries from legitimate users.\n Define how detection success is measured, designing metrics and evaluation strategies for problems where ground truth is noisy, delayed, or contested.\n Stay current on emerging AI/ML research and evaluate how new techniques (e.g., LLMs, generative AI) can be applied to our products.\n Partner with ML Engineers, Data Engineers, and Product to take detection approaches from research to production and measure their real-world impact.\n \n Desirable Skills, Knowledge, and Experience  \n \n Fraud and bots at scale. You have experience across fraud, abuse, and/or bot detection on large, high-velocity traffic. You may focus on one, but you transfer instincts between them.\n Strong fundamentals, fluent in data. You have solid applied statistics, machine learning, and AI methodology fundamentals. You choose the right technique for the problem, and are fluent with large-scale data.\n You have at least 5-7 years of experience professionally working in Data Science, ML Engineering, or Software Engineering. \n You are very comfortable with Python \u0026 SQL in production environments.\n \n Bonus points \n \n At home in ground truth ambiguity. Building detections when ground truth is scarce is the heart of this job. You make real progress with weak, delayed, or absent labels and you're energized by adversaries that fight back.\n You don't burn signals. You understand (or are curious to learn) how to act on detections without tipping your hand, knowing that how you deploy and respond can erode your future visibility.\n Pragmatic about complexity. You know when a simple solution beats a complex one, and you don't chase small gains at disproportionate cost.\n Disciplined in code. You apply strong programming and engineering best practices in both research and production code.\n Impact-driven and clear. You connect your work to business impact and communicate clearly across technical and non-technical stakeholders.\n \n Compensation \n Compensation may be adjusted depending on work location.\n \n  For New York City based hires: Estimated annual salary of $185,000 - $231,000.\n \n Equity \n This role is eligible to participate in Cloudflare’s equity plan.\n Benefits \n Cloudflare offers a complete package of benefits and programs to support you and your family.  Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun!  The below is a description of our benefits for employees in the United States, and benefits may vary for employ","salary_min":185000,"salary_max":231000,"location":"Hybrid","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["generative-ai","llm","cloud","data-science"],"apply_url":"https://boards.greenhouse.io/cloudflare/jobs/8042547?gh_jid=8042547","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-15T00:45:56Z","expires_at":"2026-08-15T14:09:57.996669Z","created_at":"2026-07-15T14:11:16.38206Z","updated_at":"2026-07-16T14:09:58.110127Z","company_name":"Cloudflare","company_slug":"cloudflare","company_logo_url":"https://www.google.com/s2/favicons?domain=cloudflare.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d5817836-ec6a-4a44-8482-6cb7a1c60532"},{"id":"394498a7-3e09-4b7d-9dc4-98c2d5cce6a3","company_id":"ccb23d77-c69e-462b-a941-02ce99527e78","title":"Software Engineer I (Data Eng infra)","slug":"software-engineer-i-data-eng-infra-ce880ce9","description":"Who we are \n Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.\n The Aurora Driver  will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone.\n  \n At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit  aurora.tech  or follow us on  LinkedIn .\n  \n What we are looking for \n Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. \n We are seeking a talented and experienced Software Engineer to join our data engineering and infrastructure team. In this role, you will be working with our seasoned engineers and contribute to the design, development, and maintenance of our data platform, building the scalable and reliable systems that enable our organization to leverage data for insights and product innovation. You will work on the core data lake and data warehouse ecosystem infrastructure, data pipelines, and tools that process data at massive scale, ensuring it is accessible, high-quality, and secure.\n In this role, you will \n \n Design, build, and maintain robust and scalable data pipelines and ETL/ELT processes to ingest, transform, and load data from various sources into our data warehouse.\n Develop and manage data infrastructure components using AWS cloud services and infrastructure-as-code tools like Terraform.\n Collaborate with data scientists, analysts, autonomy engineering teams and product teams to understand their data needs and build solutions that meet their requirements.\n Optimize data processing systems for performance, reliability, and cost-efficiency.\n Implement monitoring, alerting, and logging for data pipelines and infrastructure to ensure operational stability.\n Champion best practices in data governance, data quality, and security.\n \n Required Qualifications \n \n Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.\n 1+ years of recent professional experience in software engineering, with a focus on data-related projects.\n Proficiency in at least one programming language commonly used for data engineering (e.g., Python, Go or C++).\n Preliminary experience with big data processing frameworks like Apache Spark, Flink, Kinesis Data Stream, or similar technologies.\n Hands-on experience with cloud platforms (AWS, GCP, or Azure) and their data services (e.g., S3, Redshift, BigQuery, Glue).\n Strong knowledge of SQL and experience working with relational and NoSQL databases.\n Preliminary knowledge of data analytics infrastructure, including data transformation tools such as DBT and visualization frameworks and tools\n Experience with building and managing data pipelines using an orchestrator like Apache Airflow.\n Able to systematically approach open-ended questions to identify pragmatic data solutions that scale\n Able to work effectively in a highly cross-functional, fast-moving and high-stakes environment\n Proven ability to communicate technical, data-driven solutions to both technical and non-technical audiences across stakeholders\n \n Desirable Qualifications  \n \n Experience with data warehousing solutions like Snowflake or data lake architectures.\n Familiarity with modern data stack tools and practices.\n A passion for building elegant, scalable, and maintainable systems.\n Experience using Amazon Web Services (AWS) tools\n \n The base salary wage range for this position is $116K-$174K per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits. \n  #LI-SP1 \n Working at Aurora At Aurora, we bring together extraordinarily talented and experienced people united by the strength of our values. We operate with integrity, set outrageous goals, and build a culture where we win together — all without any jerks.\n We believe in-person work increases collaboration, empathy and our ability to lead effectively. As a result, we operate in a hybrid work environment where Aurorans are in office at least 3 days per week.\n Our Careers page provides insight into what it is like to work at Aurora, and you can find all the latest updates in our Newsroom .\n Our commitment to safety \n At the core of everything we do is our commitment to safety. Building best-in-class self-driving technology will take time, and we believe that each employee at ","salary_min":116000,"salary_max":174000,"location":"Mountain View, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["data-pipeline","autonomous-vehicles","cloud","data-science","infrastructure"],"apply_url":"https://aurora.tech/jobs/8628066002?gh_jid=8628066002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T13:24:28Z","expires_at":"2026-08-15T14:05:24.523638Z","created_at":"2026-07-15T14:06:40.845277Z","updated_at":"2026-07-16T14:05:24.669605Z","company_name":"Aurora Innovation","company_slug":"aurora-innovation","company_logo_url":"https://www.google.com/s2/favicons?domain=aurora.tech\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/394498a7-3e09-4b7d-9dc4-98c2d5cce6a3"},{"id":"536847ab-380b-4023-a67d-e6f42968d89e","company_id":"ccb23d77-c69e-462b-a941-02ce99527e78","title":"Senior Software Engineer (Data Engineering and Infrastructure)","slug":"senior-software-engineer-data-engineering-and-infrastructure-fbb63209","description":"Who we are \n Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.\n The Aurora Driver  will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone.\n  \n At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit  aurora.tech  or follow us on  LinkedIn .\n  \n What we are looking for \n Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We are seeking a talented and experienced Software Engineer to join our data engineering and infrastructure team. In this role, you will be a key contributor to the design, development, and maintenance of our data platform, building the scalable and reliable systems that enable our organization to leverage data for insights and product innovation. You will work on the core data lake and data warehouse ecosystem infrastructure, data pipelines, and tools that process data at massive scale, ensuring it is accessible, high-quality, and secure.\n In this role, you will \n \n Design, build, and maintain robust and scalable data pipelines and ETL/ELT processes to ingest, transform, and load data from various sources into our data warehouse.\n Develop and manage data infrastructure components using AWS cloud services and infrastructure-as-code tools like Terraform.\n Collaborate with data scientists, analysts, autonomy engineering teams and product teams to understand their data needs and build solutions that meet their requirements.\n Optimize data processing systems for performance, reliability, and cost-efficiency.\n Implement monitoring, alerting, and logging for data pipelines and infrastructure to ensure operational stability.\n Champion best practices in data governance, data quality, and security.\n Work closely with other senior team members and management to improve the data ecosystem toolings, refine user experience, and continuously polish team roadmap.\n \n Required Qualifications \n \n Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.\n 5+ years of professional experience in software engineering, with a focus on data-related projects.\n Proficiency in at least one programming language commonly used for data engineering (e.g., Python, Go or C++).\n Solid experience with big data processing frameworks like Presto/Trino, EMR, Apache Spark, Flink, Kinesis Data Stream, or similar technologies.\n Hands-on experience with cloud platforms (AWS, GCP, or Azure) and their data services (e.g., S3, Redshift, BigQuery, Glue).\n Strong knowledge of SQL and experience working with relational and NoSQL databases.\n Intermediate knowledge of data analytics infrastructure, including data transformation tools such as DBT and visualization frameworks and tools\n Experience with building and managing data pipelines using an orchestrator like Apache Airflow.\n Able to systematically approach open-ended questions to identify pragmatic data solutions that scale\n Able to work effectively in a highly cross-functional, fast-moving and high-stakes environment\n Proven ability to communicate technical, data-driven solutions to both technical and non-technical audiences across stakeholders\n \n Desirable Qualifications  \n \n Experience with AI toolings, LLM and agentic frameworks\n Experience with data warehousing solutions like Snowflake or data lake architectures.\n Familiarity with modern data stack tools and practices.\n A passion for building elegant, scalable, and maintainable systems.\n Experience using Amazon Web Services (AWS) tools\n \n The base salary range for this position is $146K-$234K per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits. \n  #LI-SP1 \n Working at Aurora At Aurora, we bring together extraordinarily talented and experienced people united by the strength of our values. We operate with integrity, set outrageous goals, and build a culture where we win together — all without any jerks.\n We believe in-person work increases collaboration, empathy and our ability to lead effectively. As a result, we operate in a hybrid work environment where Aurorans are in office at least 3 days per week.\n Our Careers page provides insight into what it is like to work at Aurora, and you can find all the latest updates in our Newsroom .\n Our c","salary_min":146000,"salary_max":234000,"location":"Pittsburgh, PA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","data-pipeline","cloud","llm","autonomous-vehicles","infrastructure","data-science","data-engineering"],"apply_url":"https://aurora.tech/jobs/8628064002?gh_jid=8628064002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T13:23:27Z","expires_at":"2026-08-15T14:05:24.307008Z","created_at":"2026-07-15T14:06:40.677939Z","updated_at":"2026-07-16T14:05:24.454033Z","company_name":"Aurora Innovation","company_slug":"aurora-innovation","company_logo_url":"https://www.google.com/s2/favicons?domain=aurora.tech\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/536847ab-380b-4023-a67d-e6f42968d89e"},{"id":"58ddb548-32cb-47ff-9778-f85baf797bcf","company_id":"a0000000-0000-0000-0000-000000000003","title":"Senior Data Engineer, Public Sector","slug":"senior-data-engineer-public-sector-8cb646e9","description":"Senior Data Engineer, Public Sector\n As a Data Engineer for the Public Sector business unit, you will build Scale's analytical and business-intelligence infrastructure. Scale's customers process millions of tasks through our APIs, and we're looking for a talented Data Engineer to build scalable solutions to support this growth. You will have widespread purview, with responsibility for understanding, mining, aggregating, and exposing data across the entire business unit to support timely and efficient decision-making and data exploration. You will also implement Scale's data warehouse, data mart, and business intelligence reporting environments, and help users transition their workflows to these systems. \n This role requires collaboration with leadership and cross-functional teams to solve complex problems and develop sustainable, scalable data solutions. Your responsibilities will include both ad-hoc analyses and the creation of core data models and pipelines, directly impacting how Scale operates and evaluates its performance.\n You will:\n \n Work with operations, finance, and engineering to drive the development of pipelines that provide single-source-of-truth foundational accuracy\n Continually improve ongoing data pipelines and simplify self-service support for business stakeholders\n Perform regular system audits, and create data quality tests to ensure complete and accurate reporting of data/metrics\n Develop repeatable, scalable analytical solutions, such as data models, improved pipelines, or better underlying tables\n Have an active Secret security clearance (Top Secret preferred) \n \n Ideally You’d Have:\n \n 5+ years of relevant work experience in a role requiring application of data modeling and analytic skills\n Ability to create extensible and scalable data schema and pipelines that lay the foundation for downstream analysis\n Mastery of SQL and relational databases; experience with programming languages (e.g., Python/R)\n Experience building a reliable transformation layer and pipelines from ambiguous business processes using tools such DBT to create a foundation for data insights\n \n  \n Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined during the interview process based on work location and additional factors, including job-related skills, experience, qualifications, interview performance, and relevant education or training. Scale employees in eligible roles are also granted equity based compensation, subject to Board of Director approval. Your recruiter can share more about the specific salary range for your preferred location during the hiring process, and confirm whether the hired role will be eligible for equity grant. You'll also receive benefits including, but not limited to: comprehensive health, dental and vision coverage, retirement benefits, a learning and development stipend, and generous PTO. Additionally, this role may be eligible for additional benefits such as a commuter stipend. \n The base salary range for this full-time position in the location of Washington DC is:\n $200,000 — $250,000 USD \n PLEASE NOTE:  Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants. \n About Us: \n At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst \u0026 Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications. \n We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.  \n We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at accommodations@scale.com. Please see the United States Department of Labor's Know Your Rights poster for additional information. \n We comply with the United States Department of Labor's Pay Transparency provision .  \n PLEASE NOTE: We collect, retain and use personal d","salary_min":200000,"salary_max":250000,"location":"Washington, DC","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","fine-tuning","data-engineering","data-science"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4713597005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-11T02:29:10Z","expires_at":"2026-08-15T14:01:43.155302Z","created_at":"2026-07-12T14:01:20.981859Z","updated_at":"2026-07-16T14:01:43.275975Z","company_name":"Scale AI","company_slug":"scale-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=scale.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/58ddb548-32cb-47ff-9778-f85baf797bcf"},{"id":"34327561-6461-4c2b-9f53-2e7f3bfbf3f1","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Staff Data Scientist, Finance \u0026 Business Ops","slug":"staff-data-scientist-finance-business-ops-3620397e","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n Pinterest is seeking an experienced Staff Data Scientist to join our Finance \u0026 Business Operations team. This is a hybrid data-science / applied-AI / product-engineering role inside Pinterest's CFO organization. It sits at the intersection of forecasting and finance analytics, internal tool-building, and AI adoption — and the person in it is expected to operate across all three.\n The core mandate is to make the CFO org's forecasting and planning work faster, be more  rigorous, and more self-serve. In practice that has meant owning a forecasting product end to end (data pipeline through user-facing UI), partnering directly with Finance, BizOps, and Core/Monetization stakeholders to embed it in their workflows, and turning the company's emerging AI platform capabilities into tools that finance teams actually use day to day.\n This is a high-autonomy, high-trust individual-contributor role with broad cross-functional reach. \n  \n What you'll do: \n \n Own forecasting tooling end to end. Build and maintain the team's primary forecasting workbench — from the underlying data and forecast logic through the interactive web UI that planners use to create, adjust, and review forecasts. This spans baseline vs. adjusted forecast modeling, scenario/delta workflows, backtesting, and diagnostics (year-over-year and month-over-month seasonality, engagement rates, and similar).\n Ship product, not just analysis. Design and build user-facing features: chart and visualization work, guided onboarding, history/audit views, region and time-grain filtering, performance optimization, and the kind of polish and bug-fixing that makes an internal tool feel like a real product. Instrument usage (collect and analyze raw logs) and let adoption data drive the roadmap.\n Drive AI adoption across Finance \u0026 BizOps. Take platform-level AI capabilities and turn them into concrete, trusted tools for finance users. Bring structured business cases (not wishlists) to platform/IT partners, pilot new capabilities, and write the enablement material — walkthroughs, documentation, \"where to get started\" guidance — that gets non-technical teams productive.\n Stay ahead of the AI capability curve. A significant part of this role is forward-looking: continuously read and interpret AI research (papers, model and tooling releases) and translate it into a grounded point of view on what will be possible in the next 6–12 months. Track the engineering roadmap closely, understand what platform capabilities are landing and when, and connect those dots to concrete opportunities for the CFO org — so the team builds for where AI is going, not just where it is today.\n Set AI strategy and guide executives. Turn that capability foresight into strategy: shape the CFO org's AI roadmap, prioritize where to invest, and advise senior leaders and executives on what's real, what's hype, and what to bet on. Communicate complex AI and technical trade-offs in plain, decision-ready terms, and act as a trusted technical advisor in executive conversations.\n Deliver recurring finance analytics. Support core CFO-org deliverables: budget-vs-actuals (BVAs), variance commentary, executive slide/deck preparation, and metric diagnostics (e.g., MAU and revenue diagnostics), including catching and resolving data-quality issues.\n Partner broadly and communicate clearly. Work directly with Finance, BizOps, Monetization, and platform/IT stakeholders. Translate ambiguous business questions into tooling and analysis, post clear release notes and stakeholder updates, and run live walkthroughs and training sessions.\n Set technical and analytical standards. raise the bar on rigor (validation, backtesting, sound metric definitions), make pragmatic build-vs-buy and scope calls, and create artifacts and documentation durable enough to outlive any single contri","salary_min":164695,"salary_max":339078,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["agents","data-pipeline","llm","data-science"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=8036273","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T15:59:18Z","expires_at":"2026-08-15T14:09:23.913817Z","created_at":"2026-07-12T14:07:55.214517Z","updated_at":"2026-07-16T14:09:24.031949Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/34327561-6461-4c2b-9f53-2e7f3bfbf3f1"},{"id":"8e37b314-f237-44dc-a850-dd58524233c1","company_id":"19a78c6a-11dc-4d21-8273-0d2d2bad39b1","title":"Staff Data Scientist","slug":"staff-data-scientist-9bba8726","description":"Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.\n As a Staff Data Scientist, you’ll lead the design and development of scalable ML systems for use cases such as menu recommendation, demand forecasting, offer targeting, and guest personalization. You will serve as a technical thought partner across teams, set best practices, and influence the roadmap for ML-driven products that support key business outcomes. Your work will directly shape strategic decisions and enhance customer experience at scale.  \n This role is for a current vacancy.\n A day in the life (Responsibilities) \n \n Own the full machine learning lifecycle—from problem framing and data exploration to modeling, deployment, and monitoring—for mission-critical initiatives.\n Design and implement advanced ML and statistical models that improve product performance, operational efficiency, or customer insights.\n Collaborate with engineers, product managers, and business stakeholders to define project scope, success metrics, and integration strategy.\n Guide architectural decisions, set modeling standards, and champion best practices for experimentation, validation, and productionization.\n Mentor other data scientists and raise the technical bar through design reviews, feedback, and sharing domain expertise.\n Proactively identify areas where data science can create business value and lead cross-functional efforts to drive those opportunities forward.\n Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team.\n \n  \n What you'll need to thrive (Requirements) \n \n 5+ years of experience in data science with a proven track record of delivering production ML systems that drive measurable impact.\n Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.\n Experience working with real-world product data at scale and translating ambiguous problems into well-scoped ML solutions.\n Experience with distributed data processing and training, real-time inference, and ML Ops frameworks\n Prior experience mentoring other data scientists or acting as a tech lead.\n Experience leading experimentation (e.g., A/B testing), causal inference, and real-time decision systems.\n Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).\n Strong grasp of software engineering principles including modular design, version control, testing, and CI/CD.\n Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock.\n Excellent communication skills and the ability to influence both technical and non-technical stakeholders.\n Strong business acumen with the ability to align technical solutions with company goals.\n \n Bonus ingredients* : \n \n An advanced degree in Computer Science, Statistics, or a related STEM field is preferred.\n Familiarity with MLOps tooling for monitoring, drift detection, retraining, and explainability.\n Experience fine-tuning LLMs and applying reinforcement learning from human feedback (RLHF) to improve model performance and alignment.\n \n  \n AI at Toast \n At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.\n Our Total Rewards Philosophy  We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at  https://careers.toasttab.com/toast-benefits .\n #LI-Remote\n The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits. \n Pay Range \n $127,000 — $203,000 CAD \n How Toast Uses AI in its Hiring Process \n Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focus","salary_min":127000,"salary_max":203000,"location":"Canada","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["deep-learning","tensorflow","reinforcement-learning","llm","mlops","pytorch","fine-tuning","data-science"],"apply_url":"https://careers.toasttab.com/jobs?gh_jid=8052293","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T20:25:38Z","expires_at":"2026-08-15T14:10:30.495588Z","created_at":"2026-07-09T14:09:45.188959Z","updated_at":"2026-07-16T14:10:30.632055Z","company_name":"Toast","company_slug":"toast","company_logo_url":"https://www.google.com/s2/favicons?domain=pos.toasttab.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8e37b314-f237-44dc-a850-dd58524233c1"},{"id":"f04f6e13-ccf2-458b-8576-e7fa94481050","company_id":"19a78c6a-11dc-4d21-8273-0d2d2bad39b1","title":"Staff Data Scientist","slug":"staff-data-scientist-317fda4d","description":"Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy.\n As a Staff Data Scientist, you’ll lead the design and development of scalable ML systems for use cases such as menu recommendation, demand forecasting, offer targeting, and guest personalization. You will serve as a technical thought partner across teams, set best practices, and influence the roadmap for ML-driven products that support key business outcomes. Your work will directly shape strategic decisions and enhance customer experience at scale.\n A day in the life (Responsibilities) \n \n Own the full machine learning lifecycle—from problem framing and data exploration to modeling, deployment, and monitoring—for mission-critical initiatives.\n Design and implement advanced ML and statistical models that improve product performance, operational efficiency, or customer insights.\n Collaborate with engineers, product managers, and business stakeholders to define project scope, success metrics, and integration strategy.\n Guide architectural decisions, set modeling standards, and champion best practices for experimentation, validation, and productionization.\n Mentor other data scientists and raise the technical bar through design reviews, feedback, and sharing domain expertise.\n Proactively identify areas where data science can create business value and lead cross-functional efforts to drive those opportunities forward.\n Leverage cutting edge AI tools to enhance your development workflow, improve velocity, and help pioneer new approaches to building - contributing to a culture of innovation and productivity across the team.\n \n  \n What you'll need to thrive (Requirements) \n \n 7+ years of experience in data science with a proven track record of delivering production ML systems that drive measurable impact.\n Deep knowledge of statistical modeling, machine learning (e.g., tree-based models, time series, deep learning), and model evaluation.\n Experience working with real-world product data at scale and translating ambiguous problems into well-scoped ML solutions.\n Experience with distributed data processing and training, real-time inference, and ML Ops frameworks\n Prior experience mentoring other data scientists or acting as a tech lead.\n Experience leading experimentation (e.g., A/B testing), causal inference, and real-time decision systems.\n Proficiency in Python and SQL, and experience with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).\n Strong grasp of software engineering principles including modular design, version control, testing, and CI/CD.\n Hands-on experience with cloud platforms (preferably AWS), including tools like SageMaker, Athena, Glue, DynamoDB, and Bedrock.\n Excellent communication skills and the ability to influence both technical and non-technical stakeholders.\n Strong business acumen with the ability to align technical solutions with company goals.\n Experience building services on top of LLMs in a large scale production environment.\n \n Bonus ingredients* : \n \n An advanced degree in Computer Science, Statistics, or a related STEM field is preferred.\n Familiarity with MLOps tooling for monitoring, drift detection, retraining, and explainability.\n Experience fine-tuning LLMs and applying reinforcement learning from human feedback (RLHF) to improve model performance and alignment.\n \n  \n AI at Toast \n At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.\n Our Total Rewards Philosophy  We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at  https://careers.toasttab.com/toast-benefits .\n #LI-Remote\n The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits. You can learn more about how we align pay with local labor markets in our Geographic Pay Zone Philosophy . \n Zone A\n $170,000 — $272,000 USD \n Zone B\n $148,000 — $237,000 USD \n Zone C\n $133,000 — $213,000 USD \n How Toast Uses AI in its Hiring Process \n Throughout ","salary_min":133000,"salary_max":213000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","mlops","pytorch","fine-tuning","reinforcement-learning","tensorflow","deep-learning","data-science"],"apply_url":"https://careers.toasttab.com/jobs?gh_jid=8029049","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T20:23:10Z","expires_at":"2026-08-15T14:10:30.383797Z","created_at":"2026-07-09T14:09:45.268862Z","updated_at":"2026-07-16T14:10:30.539586Z","company_name":"Toast","company_slug":"toast","company_logo_url":"https://www.google.com/s2/favicons?domain=pos.toasttab.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f04f6e13-ccf2-458b-8576-e7fa94481050"},{"id":"53df0b7f-aa7f-4625-898a-170692e922fd","company_id":"19a78c6a-11dc-4d21-8273-0d2d2bad39b1","title":"Data Scientist II","slug":"data-scientist-ii-95683f8f","description":"Toast is driven by building the restaurant platform that helps restaurants adapt, take control, and get back to what they do best: building the businesses they love.\n Toast is revolutionizing the way the restaurant industry does business by pairing technology with an extraordinary commitment to customer success. We help restaurants streamline operations, increase revenue, and deliver amazing guest experiences through our platform that combines restaurant point of sale, guest-facing technology, and award-winning customer support. Join us as we empower the restaurant community to delight guests, do what they love, and thrive.  This role is for a current vacancy.\n Bready* to make a change? \n The Toast AI Engineering team is seeking a Data Scientist to embed data science capabilities into the Toast platform by partnering with engineers and product managers to develop statistical and machine learning models that power key product lines.\n About this Roll* (Responsibilities) : \n \n Apply a diverse set of expertise including data mining, statistical analysis and machine learning to deliver impactful, objective, and actionable data insights that enable informed business and product decisions\n Collaborate with cross-functional teams, including sales, marketing, and product, to identify business opportunities and develop data-driven solutions that drive growth and engagement.\n Partner with line of business teams and collaborate with product managers, engineers and data scientists to foster data-driven decisions that yield significant impacts \n Able to effectively communicate analysis, insights and recommendations to high-level business partners in verbal, visual and written formats\n Thrive in a dynamic and rapidly evolving environment\n \n Do you have the right ingredients* (Requirements) ? \n \n Bachelors in computer science, engineering, math, statistics, economics, or other quantitative discipline; Masters preferred.\n 2+ years of data science experience in an industry environment.\n Have solid statistical and machine learning foundations. Familiar with machine learning concepts (e.g. regression/classification, clustering, offline/online model evaluation). \n Experience with advanced machine learning techniques, including supervised and unsupervised learning, graph algorithms, deep learning (e.g., NLP), recommendation systems, and generative AI.\n Experience with Python and SQL, and ML frameworks (e.g. scikit-learn, Tensorflow, PyTorch)\n Experience with cloud solutions, preferably with AWS tooling (e.g. SageMaker, DynamoDB, Athena, Glue, etc.)\n Experience with model workflow orchestration tool (e.g. Airflow)\n Experience collaborating with engineers, product managers, and other cross-functional teams\n Excellent verbal and written communication skills\n Ability to communicate sophisticated quantitative analysis in a clear, precise, and actionable manner.\n \n Special Sauce* (Nice to Haves):  \n \n Experience working on LLM applications, including prompting, RAG, and evaluation.\n Experience in software engineering best practices and tools including object-oriented programming, test-driven development, CI/CD, git, shell scripting, task orchestration.\n Experience shipping machine learning systems in production environments.\n Experience in A/B testing and other experimentation methodologies for effective product launch measurement.\n \n  \n AI at Toast \n At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.\n Our Total Rewards Philosophy  We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at  https://careers.toasttab.com/toast-benefits .\n The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits. \n Pay Range \n $110,000 — $136,000 CAD \n How Toast Uses AI in its Hiring Process \n Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focused on your conversation. All hiring decisions are","salary_min":110000,"salary_max":136000,"location":"Canada","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["tensorflow","deep-learning","nlp","generative-ai","llm","pytorch","cloud","data-science"],"apply_url":"https://careers.toasttab.com/jobs?gh_jid=8052241","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T20:16:37Z","expires_at":"2026-08-15T14:10:29.290407Z","created_at":"2026-07-09T14:09:43.741168Z","updated_at":"2026-07-16T14:10:29.414512Z","company_name":"Toast","company_slug":"toast","company_logo_url":"https://www.google.com/s2/favicons?domain=pos.toasttab.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/53df0b7f-aa7f-4625-898a-170692e922fd"},{"id":"cea172f2-7ff5-4ae5-9400-c763a96f22dc","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Sr. Data Scientist, Infrastructure","slug":"sr-data-scientist-infrastructure-269a1d04","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n Pinterest brings millions of people the inspiration to create a life they love. Behind that experience is a complex infrastructure ecosystem that powers reliability, performance, measurement, and efficiency across the platform. As Pinterest grows, it’s increasingly important that we understand these systems clearly so we can make smarter decisions for both Pinners and the business.\n  \n We’re looking for a Data Scientist to join our Infrastructure Data Science team. In this role, you’ll partner with engineering and cross-functional teams to make Pinterest’s infrastructure more measurable, intelligible, and actionable. Depending on the area, your work may span app performance, shopping infrastructure, metrics quality, infrastructure governance, or site reliability. You’ll help build the data foundations, measurement systems, and analytical frameworks that enable Pinterest to optimize core technical systems and make better product and infrastructure decisions.\n  \n What you’ll do: \n In this role, you will partner closely with engineering and cross-functional teams to improve how Pinterest measures, understands, and optimizes its infrastructure:\n \n Partner with engineering teams to define, measure, and improve the health, quality, and efficiency of Pinterest’s infrastructure systems.\n Build and refine metrics, dashboards, and analytical frameworks that make complex technical systems more understandable and actionable.\n Strengthen data foundations by improving metric definitions, auditing data quality, and contributing to pipeline and measurement improvements where needed.\n Design and analyze experiments, investigations, and deep dives to quantify the impact of infrastructure changes on user experience, reliability, and business outcomes.\n Translate ambiguous technical problems into clear analyses and actionable recommendations for engineering and platform partners.\n Support high-priority investigations and decision-making related to infrastructure performance, reliability, cost, and measurement quality.\n Identify opportunities to improve how Pinterest measures and optimizes infrastructure across a range of domains, such as performance, shopping infrastructure, governance, metrics quality, and site reliability.\n \n  \n What we’re looking for: \n \n 4+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems with large-scale data.\n Bachelor’s/Master’s degree in a relevant field such as Computer Science, or equivalent experience.”\n Strong SQL and analytical programming skills, with experience working through messy, imperfect data and building reliable metrics and datasets.\n Experience partnering on or contributing to production-ready data pipelines, measurement systems, or foundational data work that improves data quality and usability.\n Solid foundation in experimentation and measurement, with the ability to design analyses, interpret results rigorously, and partner effectively with engineers and other cross-functional stakeholders.\n Demonstrated ability to translate ambiguous problems into clear analytical workstreams and actionable recommendations.\n Strong cross-functional communication skills, with the ability to explain technical findings clearly to engineering, product, and platform stakeholders.\n Ability to operate independently, prioritize across both longer-term projects and fast-turn inbound requests, and drive work forward in a dynamic environment.\n Curiosity and a builder mindset, with excitement for improving messy systems and creating more scalable, trustworthy measurement foundations.\n \n  \n In-Office Requirement Statement: \n \n We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs","salary_min":139764,"salary_max":287749,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","devops","data-science","infrastructure"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=8024966","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-07T20:19:01Z","expires_at":"2026-08-15T14:09:22.183411Z","created_at":"2026-07-09T14:08:38.685575Z","updated_at":"2026-07-16T14:09:22.304344Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/cea172f2-7ff5-4ae5-9400-c763a96f22dc"},{"id":"c79e0087-291f-4c4a-a2b7-23c8d0389df7","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Senior Data Scientist, Systems Performance","slug":"senior-data-scientist-systems-performance-690960a2","description":"Mission Summary: \n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas.\n Rigorous behavioral and system performance evaluation is critical to scaling our service and achieving Motional's long-term goals. We are seeking a Senior Data Scientist to lead initiatives that improve evaluation and testing methodologies, measure the quality and trustworthiness of our evaluation portfolio, and partner with engineering teams to monitor and strengthen the health of the evaluation ecosystem. You will help ensure Motional's performance evaluation is efficient, scientifically rigorous, and aligned with our growth priorities.\n In this role, you will lead development of evaluation methodologies and metrics that assess the quality and business relevance of solutions spanning on-road and off-board data. You will influence the evaluation signals software engineers rely on to validate that changes to the autonomy stack deliver intended improvements, conduct deep-dive analyses to understand bottlenecks in current methodologies, and prototype improvements in metrics, sampling strategy, and statistical inference. You will develop deep expertise in how evaluation signals inform launch and release decisions, weigh trade-offs across the evaluation portfolio, and provide actionable insights for designing launch criteria.\n If you are a rigorous, collaborative data scientist with a passion for improving how autonomous systems are measured and validated at scale, we encourage you to apply. \n What You’ll Be Doing: \n \n Lead the development of evaluation frameworks for the autonomous system, connecting technical problems to rigorous, data-driven approaches for measuring and validating performance. \n Collaborate closely with Functional Safety and Systems Engineering teams to ensure evaluation metrics map effectively to automotive safety standards (e.g., SOTIF, ISO 21448) and launch readiness decisions.\n Ensure evaluation metrics are reliable enough to inform safety cases and launch readiness decisions.\n Monitor the reliability of evaluation metrics and incoming performance data over time, including detecting drift, inconsistencies, and degradation in metric definitions, to ensure the evaluation ecosystem remains accurate and trustworthy.\n Drive our approach to performance analysis using data-backed statistical methods for simulation and on-road data.\n Develop new statistical analysis methods to analyze AV performance data and lead by example in applying them to real problems.\n Partner with triage operators and simulation engineers to turn raw disengagements and identified edge cases into procedural or generative scenarios, feeding them back into the simulation catalog to strengthen test coverage.\n Use fleet and evaluation data to identify edge cases in an automated manner and coverage gaps, and partner with engineering to feed novel scenarios back into the simulation catalog and strengthen test coverage.\n Build confidence in the evaluation framework through data-driven insights and clear communication of findings to technical leaders and stakeholders.\n Establish correlation between on-road and simulation data to improve how we interpret and act on evaluation results.\n Make sense of large datasets to drive insights, solve ambiguous performance questions, and communicate results effectively across teams and upward to leadership.\n Establish a self-service model for developers to understand the impact of their changes.\n Develop new metrics, interpret trends, and investigate anomalies in simulation and on-road data. \n Collaborate with developers to drive action based on these results.\n Serve as an advisor and influence collaborators across multiple teams, promote data-aware decision making, and establish best practices around the use of data.\n Mentor and collaborate with fellow engineers and foster a positive, collaborative work environment.\n Introduce the use of ML methods for performance evaluation where they add rigor and scale. \n \n What You Bring: \n \n 5+ years of industry experience solving complex problems with large datasets, with a track record of framing ambiguous questions into rigorous, data-driven analyses.\n Bachelor's or higher degree in Computer Science, Computer Engineering, Data Science, Robotics, Physics, Mathematics, or a related quantitative field. Master's or PhD preferred.\n Strong problem-solving skills: ability to break down complex performance and evaluation challenges, think logically, and remove bias from how problems are defined and assessed.\n Strong Python and SQL skills, with demonstrated expe","salary_min":149000,"salary_max":198000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","robotics","mlops","autonomous-vehicles","deep-learning","data-science"],"apply_url":"https://motional.com/open-positions/?gh_jid=7797913003#/7797913003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-07T17:01:19Z","expires_at":"2026-08-15T14:06:46.981515Z","created_at":"2026-07-09T14:06:16.041532Z","updated_at":"2026-07-16T14:06:47.100321Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c79e0087-291f-4c4a-a2b7-23c8d0389df7"},{"id":"26a6c1a9-8651-4f0f-9719-559626bfb1ec","company_id":"ec4a8bb4-3840-4054-8ccd-77e81db037af","title":"Data Scientist/Senior Data Scientist","slug":"data-scientistsenior-data-scientist-8e359427","description":"C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI \n As a member of the C3 AI Data Science team , you will work with some of the largest companies on the planet helping them build the next generation of AI-powered enterprise applications on the C3 AI Platform. You will work directly with data scientists, AI engineers, and subject matter experts to design and deploy AI capabilities that give our customers the information they need to make better decisions and accelerate their digital transformation. You will identify the right AI approaches for each problem and implement them on the C3 AI Platform so they run reliably at enterprise scale.\n Qualified candidates will have deep knowledge of modern AI and ML techniques — including large language models, agentic systems, and classical statistical methods — along with a clear understanding of their limitations and how to adapt them to large-scale production environments. Some travel is expected.\n Note: This is a client-facing position which requires travel. Candidates should have the ability and willingness to travel based on business needs. \n Responsibilities: \n \n Lead the research, design, implementation, and deployment of AI models, agentic solutions, and optimization algorithms for enterprise applications on the C3 AI Platform.\n Partner with C3 AI customers to build and scale their own AI applications on the Platform.\n Contribute to the design and implementation of new AI capabilities within the C3 AI Platform.\n Analyze model performance across enterprise deployments, diagnose issues such as poor recall or false positive rates, and recommend targeted improvements.\n Collaborate with data engineers and subject matter experts from C3 AI and customer teams to source, validate, and correctly leverage new data assets.\n \n Qualifications: \n \n MS or PhD in Computer Science, Electrical Engineering, Statistics,   Operations Research, or a related field.\n Hands-on AI experience spanning generative AI, agentic systems, supervised and unsupervised learning, and classical regression and classification.\n Strong mathematical foundation in linear algebra, calculus, probability, and statistics.\n Experience building and deploying models at scale in distributed or cloud-native environments.\n Ability to drive projects independently and collaborate effectively across technical and non-technical teams.\n Sharp, motivated, and focused on making a real impact.\n Excellent verbal and written communication skills.\n \n Preferred Qualifications: \n \n Proficiency in Python; experience with JavaScript, Java, or Scala is a plus.\n Familiarity with LLM frameworks (e.g., LangChain, LlamaIndex), vector databases, or RAG architectures.\n A portfolio of AI projects (GitHub, publications, or open-source contributions) is a plus.\n C3 AI provides excellent benefits, a competitive compensation package and generous equity plan. \n California Base Pay Range\n $136,000 — $183,000 USD \n C3 AI is proud to be an Equal Opportunity and Affirmative Action Employer. We do not discriminate on the basis of any legally protected characteristics, including disabled and veteran status.","salary_min":136000,"salary_max":183000,"location":"Redwood City, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","agents","rag","generative-ai","embeddings","data-science"],"apply_url":"https://c3.ai/job-description/8621803002?gh_jid=8621803002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-06T23:21:46Z","expires_at":"2026-08-15T14:10:33.838245Z","created_at":"2026-07-07T14:11:23.526299Z","updated_at":"2026-07-16T14:10:33.971665Z","company_name":"C3 AI","company_slug":"c3-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=c3.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/26a6c1a9-8651-4f0f-9719-559626bfb1ec"},{"id":"16cc35ff-c277-4fa2-97ba-55a0048a0b21","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Senior Data Scientist, Systems Performance","slug":"senior-data-scientist-systems-performance-cf30584b","description":"Mission Summary: \n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas.\n Rigorous behavioral and system performance evaluation is critical to scaling our service and achieving Motional's long-term goals. We are seeking a Senior Data Scientist to lead initiatives that improve evaluation and testing methodologies, measure the quality and trustworthiness of our evaluation portfolio, and partner with engineering teams to monitor and strengthen the health of the evaluation ecosystem. You will help ensure Motional's performance evaluation is efficient, scientifically rigorous, and aligned with our growth priorities.\n In this role, you will lead development of evaluation methodologies and metrics that assess the quality and business relevance of solutions spanning on-road and off-board data. You will influence the evaluation signals software engineers rely on to validate that changes to the autonomy stack deliver intended improvements, conduct deep-dive analyses to understand bottlenecks in current methodologies, and prototype improvements in metrics, sampling strategy, and statistical inference. You will develop deep expertise in how evaluation signals inform launch and release decisions, weigh trade-offs across the evaluation portfolio, and provide actionable insights for designing launch criteria.\n If you are a rigorous, collaborative data scientist with a passion for improving how autonomous systems are measured and validated at scale, we encourage you to apply. \n What You’ll Be Doing: \n \n Lead the development of evaluation frameworks for the autonomous system, connecting technical problems to rigorous, data-driven approaches for measuring and validating performance. \n Collaborate closely with Functional Safety and Systems Engineering teams to ensure evaluation metrics map effectively to automotive safety standards (e.g., SOTIF, ISO 21448) and launch readiness decisions.\n Ensure evaluation metrics are reliable enough to inform safety cases and launch readiness decisions.\n Monitor the reliability of evaluation metrics and incoming performance data over time, including detecting drift, inconsistencies, and degradation in metric definitions, to ensure the evaluation ecosystem remains accurate and trustworthy.\n Drive our approach to performance analysis using data-backed statistical methods for simulation and on-road data.\n Develop new statistical analysis methods to analyze AV performance data and lead by example in applying them to real problems.\n Partner with triage operators and simulation engineers to turn raw disengagements and identified edge cases into procedural or generative scenarios, feeding them back into the simulation catalog to strengthen test coverage.\n Use fleet and evaluation data to identify edge cases in an automated manner and coverage gaps, and partner with engineering to feed novel scenarios back into the simulation catalog and strengthen test coverage.\n Build confidence in the evaluation framework through data-driven insights and clear communication of findings to technical leaders and stakeholders.\n Establish correlation between on-road and simulation data to improve how we interpret and act on evaluation results.\n Make sense of large datasets to drive insights, solve ambiguous performance questions, and communicate results effectively across teams and upward to leadership.\n Establish a self-service model for developers to understand the impact of their changes.\n Develop new metrics, interpret trends, and investigate anomalies in simulation and on-road data. \n Collaborate with developers to drive action based on these results.\n Serve as an advisor and influence collaborators across multiple teams, promote data-aware decision making, and establish best practices around the use of data.\n Mentor and collaborate with fellow engineers and foster a positive, collaborative work environment.\n Introduce the use of ML methods for performance evaluation where they add rigor and scale. \n \n What You Bring: \n \n 5+ years of industry experience solving complex problems with large datasets, with a track record of framing ambiguous questions into rigorous, data-driven analyses.\n Bachelor's or higher degree in Computer Science, Computer Engineering, Data Science, Robotics, Physics, Mathematics, or a related quantitative field. Master's or PhD preferred.\n Strong problem-solving skills: ability to break down complex performance and evaluation challenges, think logically, and remove bias from how problems are defined and assessed.\n Strong Python and SQL skills, with demonstrated expe","salary_min":149000,"salary_max":198500,"location":"Las Vegas, Nevada, United States","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["deep-learning","mlops","autonomous-vehicles","data-pipeline","robotics","data-science"],"apply_url":"https://motional.com/open-positions/?gh_jid=7792500003#/7792500003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-02T14:03:55Z","expires_at":"2026-08-15T14:06:47.056338Z","created_at":"2026-07-03T14:05:53.429797Z","updated_at":"2026-07-16T14:06:47.197335Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/16cc35ff-c277-4fa2-97ba-55a0048a0b21"},{"id":"bc579a13-161e-4277-abd7-fbc3b1c71dc4","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Senior Data Scientist, Systems Performance","slug":"senior-data-scientist-systems-performance-1f0377b0","description":"Mission Summary: \n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas.\n Rigorous behavioral and system performance evaluation is critical to scaling our service and achieving Motional's long-term goals. We are seeking a Senior Data Scientist to lead initiatives that improve evaluation and testing methodologies, measure the quality and trustworthiness of our evaluation portfolio, and partner with engineering teams to monitor and strengthen the health of the evaluation ecosystem. You will help ensure Motional's performance evaluation is efficient, scientifically rigorous, and aligned with our growth priorities.\n In this role, you will lead development of evaluation methodologies and metrics that assess the quality and business relevance of solutions spanning on-road and off-board data. You will influence the evaluation signals software engineers rely on to validate that changes to the autonomy stack deliver intended improvements, conduct deep-dive analyses to understand bottlenecks in current methodologies, and prototype improvements in metrics, sampling strategy, and statistical inference. You will develop deep expertise in how evaluation signals inform launch and release decisions, weigh trade-offs across the evaluation portfolio, and provide actionable insights for designing launch criteria.\n If you are a rigorous, collaborative data scientist with a passion for improving how autonomous systems are measured and validated at scale, we encourage you to apply. \n What You’ll Be Doing: \n \n Lead the development of evaluation frameworks for the autonomous system, connecting technical problems to rigorous, data-driven approaches for measuring and validating performance. \n Collaborate closely with Functional Safety and Systems Engineering teams to ensure evaluation metrics map effectively to automotive safety standards (e.g., SOTIF, ISO 21448) and launch readiness decisions.\n Ensure evaluation metrics are reliable enough to inform safety cases and launch readiness decisions.\n Monitor the reliability of evaluation metrics and incoming performance data over time, including detecting drift, inconsistencies, and degradation in metric definitions, to ensure the evaluation ecosystem remains accurate and trustworthy.\n Drive our approach to performance analysis using data-backed statistical methods for simulation and on-road data.\n Develop new statistical analysis methods to analyze AV performance data and lead by example in applying them to real problems.\n Partner with triage operators and simulation engineers to turn raw disengagements and identified edge cases into procedural or generative scenarios, feeding them back into the simulation catalog to strengthen test coverage.\n Use fleet and evaluation data to identify edge cases in an automated manner and coverage gaps, and partner with engineering to feed novel scenarios back into the simulation catalog and strengthen test coverage.\n Build confidence in the evaluation framework through data-driven insights and clear communication of findings to technical leaders and stakeholders.\n Establish correlation between on-road and simulation data to improve how we interpret and act on evaluation results.\n Make sense of large datasets to drive insights, solve ambiguous performance questions, and communicate results effectively across teams and upward to leadership.\n Establish a self-service model for developers to understand the impact of their changes.\n Develop new metrics, interpret trends, and investigate anomalies in simulation and on-road data. \n Collaborate with developers to drive action based on these results.\n Serve as an advisor and influence collaborators across multiple teams, promote data-aware decision making, and establish best practices around the use of data.\n Mentor and collaborate with fellow engineers and foster a positive, collaborative work environment.\n Introduce the use of ML methods for performance evaluation where they add rigor and scale. \n \n What You Bring: \n \n 5+ years of industry experience solving complex problems with large datasets, with a track record of framing ambiguous questions into rigorous, data-driven analyses.\n Bachelor's or higher degree in Computer Science, Computer Engineering, Data Science, Robotics, Physics, Mathematics, or a related quantitative field. Master's or PhD preferred.\n Strong problem-solving skills: ability to break down complex performance and evaluation challenges, think logically, and remove bias from how problems are defined and assessed.\n Strong Python and SQL skills, with demonstrated expe","salary_min":149000,"salary_max":198500,"location":"Pittsburgh, PA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["autonomous-vehicles","deep-learning","robotics","data-pipeline","mlops","data-science"],"apply_url":"https://motional.com/open-positions/?gh_jid=7792499003#/7792499003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-02T14:03:54Z","expires_at":"2026-08-15T14:06:46.813699Z","created_at":"2026-07-03T14:05:53.340998Z","updated_at":"2026-07-16T14:06:46.93772Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/bc579a13-161e-4277-abd7-fbc3b1c71dc4"},{"id":"36984e0e-3530-4ca8-aaf1-3139be0b6476","company_id":"41d4f321-d748-4a4e-962f-dd5d23de3e43","title":"Senior Data Scientist, Systems Performance","slug":"senior-data-scientist-systems-performance-65636409","description":"Mission Summary: \n The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas.\n Rigorous behavioral and system performance evaluation is critical to scaling our service and achieving Motional's long-term goals. We are seeking a Senior Data Scientist to lead initiatives that improve evaluation and testing methodologies, measure the quality and trustworthiness of our evaluation portfolio, and partner with engineering teams to monitor and strengthen the health of the evaluation ecosystem. You will help ensure Motional's performance evaluation is efficient, scientifically rigorous, and aligned with our growth priorities.\n In this role, you will lead development of evaluation methodologies and metrics that assess the quality and business relevance of solutions spanning on-road and off-board data. You will influence the evaluation signals software engineers rely on to validate that changes to the autonomy stack deliver intended improvements, conduct deep-dive analyses to understand bottlenecks in current methodologies, and prototype improvements in metrics, sampling strategy, and statistical inference. You will develop deep expertise in how evaluation signals inform launch and release decisions, weigh trade-offs across the evaluation portfolio, and provide actionable insights for designing launch criteria.\n If you are a rigorous, collaborative data scientist with a passion for improving how autonomous systems are measured and validated at scale, we encourage you to apply. \n What You’ll Be Doing: \n \n Lead the development of evaluation frameworks for the autonomous system, connecting technical problems to rigorous, data-driven approaches for measuring and validating performance. \n Collaborate closely with Functional Safety and Systems Engineering teams to ensure evaluation metrics map effectively to automotive safety standards (e.g., SOTIF, ISO 21448) and launch readiness decisions.\n Ensure evaluation metrics are reliable enough to inform safety cases and launch readiness decisions.\n Monitor the reliability of evaluation metrics and incoming performance data over time, including detecting drift, inconsistencies, and degradation in metric definitions, to ensure the evaluation ecosystem remains accurate and trustworthy.\n Drive our approach to performance analysis using data-backed statistical methods for simulation and on-road data.\n Develop new statistical analysis methods to analyze AV performance data and lead by example in applying them to real problems.\n Partner with triage operators and simulation engineers to turn raw disengagements and identified edge cases into procedural or generative scenarios, feeding them back into the simulation catalog to strengthen test coverage.\n Use fleet and evaluation data to identify edge cases in an automated manner and coverage gaps, and partner with engineering to feed novel scenarios back into the simulation catalog and strengthen test coverage.\n Build confidence in the evaluation framework through data-driven insights and clear communication of findings to technical leaders and stakeholders.\n Establish correlation between on-road and simulation data to improve how we interpret and act on evaluation results.\n Make sense of large datasets to drive insights, solve ambiguous performance questions, and communicate results effectively across teams and upward to leadership.\n Establish a self-service model for developers to understand the impact of their changes.\n Develop new metrics, interpret trends, and investigate anomalies in simulation and on-road data. \n Collaborate with developers to drive action based on these results.\n Serve as an advisor and influence collaborators across multiple teams, promote data-aware decision making, and establish best practices around the use of data.\n Mentor and collaborate with fellow engineers and foster a positive, collaborative work environment.\n Introduce the use of ML methods for performance evaluation where they add rigor and scale. \n \n What You Bring: \n \n 5+ years of industry experience solving complex problems with large datasets, with a track record of framing ambiguous questions into rigorous, data-driven analyses.\n Bachelor's or higher degree in Computer Science, Computer Engineering, Data Science, Robotics, Physics, Mathematics, or a related quantitative field. Master's or PhD preferred.\n Strong problem-solving skills: ability to break down complex performance and evaluation challenges, think logically, and remove bias from how problems are defined and assessed.\n Strong Python and SQL skills, with demonstrated expe","salary_min":149000,"salary_max":198500,"location":"Boston, MA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["deep-learning","robotics","data-pipeline","mlops","autonomous-vehicles","data-science"],"apply_url":"https://motional.com/open-positions/?gh_jid=7792493003#/7792493003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-02T14:03:53Z","expires_at":"2026-08-15T14:06:46.907274Z","created_at":"2026-07-03T14:05:53.253362Z","updated_at":"2026-07-16T14:06:47.025454Z","company_name":"Motional","company_slug":"motional","company_logo_url":"https://www.google.com/s2/favicons?domain=motional.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/36984e0e-3530-4ca8-aaf1-3139be0b6476"},{"id":"97fea4cd-8602-4089-8c50-c9df587a4c97","company_id":"3dacb2af-b4b4-42ae-9b16-4e0203d290e4","title":"Data Scientist Manager, Engineering","slug":"engineering-manager-system-evaluation-51e51dd0","description":"About Wing:  \n Wing offers drone delivery as a safe, fast, and sustainable solution for last mile logistics. Consumer appetites for on-demand services are increasing, but current delivery methods are inefficient, costly, and contribute to road accidents and air pollution. Wing’s fleet of highly automated delivery drones can transport small packages directly from businesses to homes on-demand, in minutes. We design, build, and operate our aircraft, and offer drone delivery services on two continents. Our technology is designed to be easy to integrate into existing delivery and logistics networks, offering a scalable drone delivery solution for a broad range of businesses. Wing is a part of Google's parent company, Alphabet, and our mission is to create the preferred means of delivery for the planet. If you're ready to do the greatest work of your life, come join us. \n About the Role: \n Wing is looking for a Data Scientist Manager, Engineering  to join our SimEval team. This role is hybrid based in Palo Alto, CA .\n As Wing scales its autonomous drone delivery fleet, the volume of simulation and real-world operational flight data is growing exponentially. To accelerate R\u0026D, while maintaining our ability to operate reliability at scale, we are looking for a Data Scientist Manager, Engineering to join the SimEval team. This role will operate at the intersection of engineering, simulation, and analytics, bridging the gap between operational data and our technical roadmap.\n In this role, you will lead the System Evaluation team that connects operations and engineering, transforming real-world data into actionable insights that inform engineering direction and ensure scalable and reliable systems. \n What You’ll Do:  \n \n Lead, coach, and grow a team of technical data analysts responsible for distilling complex data into actionable recommendations that inform engineering direction and ensure scalable, reliable systems.\n Design and deliver the evaluation workflows, automated triage strategies, and analysis algorithms that aggregate engineering metrics into actionable feedback for engineering leadership.\n Define the metrics, acceptance criteria, and success thresholds that govern our continuous software releases.\n Develop new statistical methods and data pipelines to quantify performance and identify behavioral regressions across our operational domains.\n Connect real-world operational findings directly to the engineering roadmap, and leverage simulation to predict performance of the system with new features and releases.\n Partner closely with engineering teams, flight operations and the Analytics team to turn business metrics into clear insights that drive the technical roadmap and root-cause analysis of system degradation.\n \n What You’ll Need:  \n \n 8+ years of experience in data analytics, data science, or operational analysis, including 3+ years of experience directly managing and growing analytical teams.\n B.S or M.S degree or equivalent practical experience in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field.\n Proven experience analyzing complex hardware/software systems, robotics, or massive simulation environments.\n Proven ability to design and implement robust data pipelines, dashboards, and automated alerting systems from the ground up.\n Expertise in applied statistics, experiment design, and A/B testing, with a strong track record of using these methodologies to quantify system performance.\n Strong programming and data querying skills using Python, SQL, or R to manipulate massive datasets and extract actionable insights.\n Exceptional ability to translate complex data into clear narratives, presenting analytical findings effectively to engineering partners and organizational leadership.\n The US base salary range for this full-time position is the salary range below + bonus + equity + benefits. Wing’s salary ranges are determined by role, level, and location. Your recruiter can share more about the specific salary range for your location during the hiring process. \n Salary Range\n $228,000 — $242,000 USD \n Wing is an equal opportunity employer and it is Wing's policy to comply with all applicable national, state and local laws pertaining to nondiscrimination and equal opportunity. Employment at Wing is based solely on a person's merit and qualifications directly related to professional competence. Wing does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law.\n If you have a need that requires accommodation during the interview process due to a disability or special need, please let us know by completing our  Candidate Accommodations Request Form .","salary_min":228000,"salary_max":242000,"location":"Palo Alto, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["cloud","robotics","data-pipeline","data-science"],"apply_url":"https://wing.com/careers/8606961002?gh_jid=8606961002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-01T18:48:21Z","expires_at":"2026-08-15T14:18:37.689302Z","created_at":"2026-07-03T14:17:05.920255Z","updated_at":"2026-07-16T14:18:37.816029Z","company_name":"Wing","company_slug":"wing","company_logo_url":"https://www.google.com/s2/favicons?domain=wing.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/97fea4cd-8602-4089-8c50-c9df587a4c97"},{"id":"85afcee1-b2a5-4ad7-ae35-7bc38bc79788","company_id":"053355fc-0162-4bb9-b414-cbf7679ee9c8","title":"Lead Data Scientist","slug":"analytics-lead-6bd01437","description":"About Snorkel \n At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.\n We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!\n About the Role\n Our Data \u0026 Analytics Platform team recently migrated from Redshift to Snowflake, enabled 100+ users, and centralized all business data in under three months. We are a lean team with a clear remit: ensure a single source of truth for all business data. With company-wide Snowflake adoption complete, we are hiring a Lead Data Scientist to expand our mandate to Generative AI Analytics and Snorkel’s highest-leverage data science problems. \n This is a senior individual contributor role with no direct reports; just ownership, autonomy, and impact from pioneering new insights and models and building our semantic layer, supply/demand matching algorithms, forecasting models, and other data science foundations that compound. \n How you'll allocate your time (estimates subject to change): \n \n 40% : Building and maintaining Generative AI Analytics \n 40% : Critical-path data science projects \n 20% : Partnering with Engineers, PMs, DaaS operational leads, and Finance  \n \n What You'll Do\n \n Own Generative AI Analytics: Build and maintain end-to-end infra (semantic layer, LLM tooling, evals, and agents) to analytically empower every team at Snorkel.\n Protect Quality: Work with Engineering and the Fraud Operations Lead to build, unify inputs for, and deploy fraud detection and contributor quality models.\n Optimize Marketplace: Architect search, ranking, and recommendation models to match project needs for Expert Contributors across domains and geographies.\n Improve Forecasting: Build predictive models to help Strategy \u0026 Operations and Finance elevate forecast accuracy with signals from across the business.\n Identify Leverage: Surface the next high-value data science opportunities at Snorkel and build the case for their prioritization with the Head of Data.\n Advise Leadership: Be a trusted thought partner to the Head of Data and leaders of other teams on data architecture, applied data science, and AI.\n \n Qualifications\n \n 5+ years: data science or related experience, with a track record of shipping forecasting, ranking, recommendation, or similar models into production. \n Tech Stack: SQL, Snowflake or a similar data warehouse, and Python experience. \n Modern AI Tools: Experience deploying modern AI tools (semantic layers, LLMs, evaluation frameworks) reliably into production. \n Engineering Collaboration: Proven ability to partner with Engineering teams to bridge the gap from prototype to production system. \n Agency: Strong track record of impact without a large team or detailed roadmap.\n 0-to-1 Mindset: Comfortable building foundational systems from scratch in environments where data infrastructure is still maturing. \n Partnership: Genuinely values engaging technical and operational stakeholders to fully understand a problem and build data-driven solutions. \n \n Bonus Points: Experience with Streamlit, Snowflake Cortex, AI/data labeling, A/B testing, and two-sided marketplace or data product business models.  \n Pay Transparency Notice: Depending on your work location, the target annual salary for this position can range as detailed below. Snorkel also includes benefits (including medical, dental, vision and 401(k)).\n Pay Range $130,000-$200,000 \n \n Be Your Best at Snorkel \n Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success.\n Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for em","salary_min":130000,"salary_max":200000,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","generative-ai","data-pipeline","data-science"],"apply_url":"https://job-boards.greenhouse.io/snorkelai/jobs/6104260004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-30T19:52:54Z","expires_at":"2026-08-15T14:03:53.073931Z","created_at":"2026-07-01T14:03:18.367873Z","updated_at":"2026-07-16T14:03:53.19998Z","company_name":"Snorkel AI","company_slug":"snorkel-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=snorkel.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/85afcee1-b2a5-4ad7-ae35-7bc38bc79788"},{"id":"99e67ee8-c3eb-46bf-a32c-2d1bb128889e","company_id":"83c597c2-a4b2-4517-99df-1ac8c90756d5","title":"Safety Statistician, III – Risk \u0026 Safety Analysis","slug":"safety-statistician-iii-risk-safety-analysis-27624a7c","description":"About the Company     \n At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.   \n A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners.   Now a part of the Daimler family , we are focused solely on developing software for automated trucks to transform how the world moves freight.    \n Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.    \n Meet the Team   \n As a Safety Statistician – Risk \u0026 Safety Analysis, you will play a critical role in how Torc evaluates, communicates, and makes decisions about the safety of its autonomous driving systems.   \n You will influence the design and execution of statistically rigorous analyses that inform safety assurance strategies, engineering priorities, and risk-based decision making. Your work will directly influence how safety performance and risk are measured, understood, and acted upon across the organization.   \n This is a technical role focused on applied statistics and decision support, not dashboarding, experimentation platforms, or generic ML product analytics.   \n What You’ll Do   \n \n Employ statistically sound analyses to answer high-impact safety and regulatory questions, including how system performance translates to risk   \n \n \n Apply statistical methods to quantify and assess risk using a variety of data sources including large-scale time-series data (e.g., vehicle and sensor data) and structured safety datasets   \n \n \n Bridge safety and engineering teams by translating complex analyses into information engineers can act on   \n \n \n Develop automated, production-ready analysis workflows that support continuous safety monitoring   \n \n \n Select and defend appropriate statistical approaches for sparse, noisy, or rare-event data, applying Bayesian and frequentist methods and leveraging machine learning techniques where appropriate   \n \n \n Communicate statistically defensible findings to technical leaders, safety stakeholders, and executives   \n \n What You’ll Need to Succeed   \n \n Advanced degree in Statistics or a closely related field   \n \n \n M.S. with 3+ years of experience, or   \n \n \n PhD with 1+ years of experience   \n \n \n Strong background in applied statistics, safety analysis, and risk estimation   \n \n \n Experience in autonomous vehicles, adjacent safety-critical domains (automotive, aerospace, defense, robotics, rail, etc.), or comparable actuarial experience   \n \n \n Experience working with complex, real-world datasets rather than clean or purely academic data   \n \n \n Hands-on experience using Python for analysis (SQL and/or R a plus, but not required)   \n \n \n Ability to communicate statistical concepts clearly to non-statistical audiences   \n \n \n Comfort operating independently as a technical leader in a cross-functional, distributed environment   \n \n \n Domain knowledge in Bayesian methods   \n \n Bonus Points   \n \n Experience applying Bayesian methods to estimate risk using disparate data sources (such as simulations and naturalistic driving)   \n \n \n Background applying statistics to engineering or physics-based systems   \n \n \n Familiarity with time-series analysis, uncertainty quantification, or rare-event modeling   \n \n \n Experience supporting executive or external stakeholder decision-making requiring quick turnarounds, balancing analytical rigor with timeliness   \n \n Perks of Being a Full-time Torc’r   \n Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:     \n \n A competitive compensation package that includes a bonus component and stock options   \n \n \n 100% paid medical, dental, and vision premiums for full-time employees     \n \n \n 401K plan with a 6% employer match   \n \n \n Flexibility in schedule and generous paid vacation (available immediately after start date)   \n \n \n Company-wide holiday office closures   \n \n \n AD+D and Life Insurance    \n \n At Torc, we’re committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.   \n Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply.   \n Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience.","salary_min":145900,"salary_max":175100,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"mid","tags":["robotics","autonomous-vehicles","payments","data-science"],"apply_url":"https://job-boards.greenhouse.io/torcrobotics/jobs/8600782002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-24T12:28:39Z","expires_at":"2026-08-15T14:06:20.458772Z","created_at":"2026-06-28T14:05:33.002973Z","updated_at":"2026-07-16T14:06:20.587395Z","company_name":"Torc Robotics","company_slug":"torc-robotics","company_logo_url":"https://www.google.com/s2/favicons?domain=torc.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/99e67ee8-c3eb-46bf-a32c-2d1bb128889e"},{"id":"947c3793-cc50-4399-8028-03d9136c430b","company_id":"e3915539-5a8f-4461-9f26-06366a918674","title":"Data Scientist, Air Dominance \u0026 Strike","slug":"data-scientist-air-dominance-strike-9a43e1ff","description":"Anduril Industries is a defense technology company with a mission to transform U.S. and allied military capabilities with advanced technology. By bringing the expertise, technology, and business model of the 21st century’s most innovative companies to the defense industry, Anduril is changing how military systems are designed, built and sold. Anduril’s family of systems is powered by Lattice OS, an AI-powered operating system that turns thousands of data streams into a realtime, 3D command and control center. As the world enters an era of strategic competition, Anduril is committed to bringing cutting-edge autonomy, AI, computer vision, sensor fusion, and networking technology to the military in months, not years.\n ABOUT THE TEAM\n The Air Dominance \u0026 Strike team at Anduril develops aerial and multi-domain robotic systems. The team is responsible for taking products like Fury (unmanned fighter jet) and Barracuda (air-breathing cruise missile) from concept to product. The team also develops Lattice for Mission Autonomy, Anduril’s premier software platform that enables masses of Fury, Barracuda, and other first and third party robots to collaborate across various missions. We work in close coordination with specialist teams like Perception, Motion Planning, Hardware, and Test Engineering to solve some of the hardest problems facing our customers. We are looking for software engineers and roboticists excited about creating a powerful autonomy software stack that includes computer vision, motion planning, SLAM, controls, estimation, and secure communications.\n ABOUT THE JOB \n As a Data Scientist at Anduril, you will dive into unique, complex challenges that come with the territory of high-stakes, advanced technology in the defense sector. Your expertise will drive innovation in autonomous systems, shaping the future of defense and intelligence with solutions that are deployed at unparalleled speed. If you're eager to leverage your data science skills in an environment that encourages bold ideas and offers the resources to turn them into reality, Anduril provides the perfect platform to propel your career and make a tangible difference in a world entering a new era of strategic competition. Join us and be part of the transformation that's setting new standards for military capabilities and security.\n REQUIRED QUALIFICATIONS \n \n A background in Computer Science, Mathematics, Statistics, Data Science, or a related technical field with a strong quantitative foundation.\n 3+ years of demonstrated expertise in Python for building data transformations, pipelines, and analysis tooling\n Familiarity with Unix/Linux environments, including proficiency with the command line interface and the ability to efficiently manage and navigate distributed computing systems.\n A proven track record of effectively working with large and complex datasets, as well as the capacity to quickly understand and work within established codebases and complex system architectures.\n A strong commitment to applying data science to solve real-world problems, with the ability to translate technical findings into actionable recommendations that have a tangible impact.\n Excellent communication and collaboration skills, with the ability to engage effectively with multidisciplinary teams, including engineers, product managers, and non-technical stakeholders.\n \n PREFERRED QUALIFICATIONS \n \n Experience working with Digital twin simulation, robotics or multi-agent autonomous systems\n Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and familiarity with containerization (e.g., Docker, Kubernetes) is highly beneficial.\n Knowledge of best practices in data governance, ethics, and privacy, as well as experience with data security and compliance requirements relevant to sensitive and classified information.\n Leadership experience, with the ability to mentor junior data scientists and lead project teams in the execution of complex data science initiatives.\n Experience working with terabyte-scale data, robotics data formats (e.g. MCAP, HDF5), and dataframes (e.g. Pandas, PySpark).\n US Salary Range\n $166,000 — $220,000 USD \n The salary range for this role is an estimate based on a wide range of compensation factors, inclusive of base salary only. Actual salary offer may vary based on (but not limited to) work experience, education and/or training, critical skills, and/or business considerations. Highly competitive equity grants are included in the majority of full time offers; and are considered part of Anduril's total compensation package. Additionally, Anduril offers top-tier benefits for full-time employees, including:   \n  \n Benefits \n At Anduril, we invest in our people. Our comprehensive, competitive benefits package (available at little to no cost to employees) ensures you’re supported in health, recovery, and whatever comes next.  For more information, Explore Our Benefits . \n  \n \n Protecting Yourself from Recruitment Scams \n An","salary_min":166000,"salary_max":220000,"location":"Costa Mesa, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["gpu","distributed-systems","computer-vision","cloud","payments","agents","robotics","data-science"],"apply_url":"https://boards.greenhouse.io/andurilindustries/jobs/5158247007?gh_jid=5158247007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-22T03:31:10Z","expires_at":"2026-08-15T14:07:36.197505Z","created_at":"2026-06-28T14:06:40.39801Z","updated_at":"2026-07-16T14:07:36.331903Z","company_name":"Anduril","company_slug":"anduril","company_logo_url":"https://www.google.com/s2/favicons?domain=anduril.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/947c3793-cc50-4399-8028-03d9136c430b"},{"id":"6f09fbcc-ed04-4755-82e5-c687ef25ec12","company_id":"26618e2f-35c7-42eb-8f60-bd25a7e9a0d2","title":"Senior Data Scientist, CX Analytics","slug":"senior-data-scientist-cx-analytics-f5afe4b1","description":"Ready to do the most impactful work of your career? At  Coinbase , we are uncompromising on our mission to increase economic freedom. The bar is high, the environment is intense, and we like it that way. This isn't a place for complacency, it’s a place to be pushed past your perceived limits. If you're ready to build the future of finance alongside people who refuse to settle for \"good enough,\" you belong here. Coinbase is a remote-first, but not remote-only company. Expect to get together quarterly for intense in-person working sessions called “surges.”  learn more about working at Coinbase .\n As a Senior Data Scientist on the CX Consumer Analytics team, you will serve as the foundational link between CX operations and top-line financial impact, owning the revenue calibration models, experimentation frameworks, and behavioral intelligence that connect every customer support interaction to Coinbase's asset accumulation flywheel. You will partner closely with CX Analytics Engineers, Program Managers, and Product teams to translate complex operational and behavioral data into defensible, executive-ready insights that drive measurable improvements in retention, product adoption, and automation quality.\n What you'll do: \n \n Own and evolve CX's Downstream Impact of Support (DSI) revenue calibration models, translating support interaction data into quantified revenue signals.\n Design and execute causal inference frameworks and experiments to measure the incremental impact of CX programs (Concierge, Proactive Outreach, automation interventions) on customer retention and product engagement.\n Build and maintain LLM-powered classification pipelines for CX contact taxonomy, customer friction detection, and issue attribution, partnering with Analytics Engineers to productionize models into CX's governed Source of Truth infrastructure.\n Partner with CX Program Managers and Product teams to define segmentation models and behavioral signals that enable personalized experiences and improve business outcomes.\n Maintain a high bar for statistical rigor across CX's analytics function, ensuring experimentation, causal analyses, and model outputs meet the standards required for executive reporting and regulatory defensibility.\n \n Required Skills and Experience: \n \n A BA/BS in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics) with 5+ years of relevant experience, or a PhD in a quantitative field with 3+ years of relevant experience.\n Demonstrated experience building revenue attribution or causal impact models and driving data science projects through ambiguous problem spaces in a consumer-facing or operational analytics context.\n Practical expertise applying statistical concepts including A/B testing, causal inference, and ML to real-world business problems, with a high bar for production-grade accuracy and evaluation rigor.\n Experience designing and deploying LLM-based classification or NLP pipelines for operational or customer-facing use cases.\n Ability to influence cross-functional stakeholders by synthesizing complex model outputs into clear, actionable narratives for executive and product audiences.\n Demonstrates the ability to responsibly use generative AI tools and copilots (e.g., LibreChat, Gemini, Glean) in daily workflows, continuously learn as tools evolve, and apply human‑in‑the‑loop practices to deliver business‑ready outputs and drive measurable improvements in efficiency, cost, and quality.\n Pay Transparency Notice: Base salary varies by location (see range below). Total compensation may also include equity and bonus eligibility, and benefits (medical, dental, vision, 401(k)). \n  \n Annual base salary range (excluding equity and bonus):\n $180,370 — $212,000 USD \n \n Application Limit: Candidates may submit a maximum of 3 applications within a 6-month period.\n Equal Opportunity Employer: Coinbase is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or genetic information. Applicants with criminal histories will be considered consistent with applicable federal, state, and local laws. \n US Applicants: View Employee Rights , Know Your Rights , and E-Verify Notice of Participation. \n Accommodations: If you are an individual with a disability who needs a reasonable accommodation, email us your request and contact info at accommodations[at]coinbase.com. Need screen reading technology? Click here to download a free compatible screen reader and view the tutorial . \n Data Privacy \u0026 Arbitration: By submitting your application, you agree to our Candidate Privacy Notice . US applicants: By submitting your application, you agree to Arbitration of Disputes .","salary_min":180370,"salary_max":212000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["code-generation","llm","generative-ai","nlp","data-science"],"apply_url":"https://www.coinbase.com/careers/positions/8009392?gh_jid=8009392","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-16T15:12:04Z","expires_at":"2026-08-15T14:09:49.732122Z","created_at":"2026-06-28T14:08:51.452766Z","updated_at":"2026-07-16T14:09:49.874751Z","company_name":"Coinbase","company_slug":"coinbase","company_logo_url":"https://www.google.com/s2/favicons?domain=www.coinbase.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6f09fbcc-ed04-4755-82e5-c687ef25ec12"},{"id":"55801a80-235c-4509-bc5c-551db3ccac1d","company_id":"12105b3e-eb1d-4a92-95b6-855042facaf1","title":"Staff Data Scientist AI/ML","slug":"staff-data-scientist-semantic-substrate-incubation-3f615ff1","description":"At Qualtrics, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. But we are more than a platform—we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers. When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that’s work worth doing.\n  \n Staff Data Scientist: Semantic Substrate Incubation  \n Why We Have This Role \n At Semantic Substrate Incubation, we are drowning in data but starving for meaning. As our lead data scientist, you will bridge this \"Meaning Gap\" by turning raw, chaotic event logs into an intelligent, concept-linked graph—the Semantic Brain. You will move past basic chat interfaces to architect an Identity-Anchored World Model that allows LLMs to understand complex enterprise ideas like \"High-Value Churn Risk\" and drive autonomous, agentic decisions. Working alongside a tight-knit team of researchers and production engineers, your work will directly define how the next generation of AI comprehends the business world.\n How You’ll Find Success \n \n Thrives in Ambiguity: Operates with a zero-to-one startup mentality. You don't need a map; you look at complex, unstructured data chaos and naturally enjoy building foundational AI products and data pipelines from scratch.\n Bridges Science and Engineering: Fluidly moves between deep applied AI research and robust production engineering, ensuring brilliant theories actually scale in production.\n Customer-Centric Translator: Enjoys working directly with pilot partners and customers, listening to their unique business pain points, and translating them into technical requirements and concrete industry ontologies.\n Principled Technical Leader: Takes ownership of the technical vision, setting a high bar for architectural excellence while mentoring and elevating the engineering team around you.\n Rigorous and Evidence-Driven: Rejects guesswork. You lean heavily on simulation, validation, and off-policy evaluation to ensure AI recommendations are grounded in reality.\n \n How You’ll Grow \n \n Pioneer Agentic AI: You will be at the absolute bleeding edge of LLM orchestration and world modeling, setting industry standards for how enterprises deploy autonomous agents.\n Expand Technical Authorship: Refine your voice as an industry thought leader with active support to publish papers, write technical books, or speak at major global AI conferences.\n Executive \u0026 Strategic Visibility: Shape the foundational AI product roadmap of the company, giving you direct influence over strategic business decisions and high-level customer relationships.\n \n Things You’ll Do \n \n Map fragmented data to human-readable terms by leading the discovery and mapping of raw event logs to Vertical Ontologies (Industry Knowledge Packs).\n Accelerate AI accuracy by 60% by designing and deploying a Concept Graph that anchors the substrate, utilizing verified profile IDs instead of session data for memory.\n Train autonomous agents efficiently by building the logic for Reward Signal Extraction and Context-Aware actioning to infer KPIs directly from interaction logs, avoiding traditional delayed-reward bottlenecks.\n Reduce agentic action risk by 40% by utilizing Off-Policy Evaluation (OPE) and action-conditional world models to simulate high-value scenarios and ground recommendations.\n Avoid the \"Services Trap\" and enable scale by engineering automated systems that allow 80% of the team's context mapping to be executed seamlessly without manual intervention.\n \n What We’re Looking For On Your Resume \n \n A Proven Tracker Record in AI/ML: Broad capability delivering high-impact AI systems at scale (typically requires around 10+ years of professional data science experience).\n Deep Graph Expertise: Hands-on experience designing, implementing, and querying graph databases, with specific, deep technical proficiency in AWS Neptune and SPARQL.\n Production-Level Data Pipelines: Extensive experience with Apache Spark (PySpark/Scala) for large-scale distributed data processing and ETL optimization on massive datasets.\n Modern LLM Orchestration: Direct, practical experience building sophisticated applications using frameworks like LangChain, LlamaIndex, or equivalent ag","salary_min":206500,"salary_max":271000,"location":"Seattle, WA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","cloud","data-pipeline","llm","healthcare","agents","data-science"],"apply_url":"https://www.qualtrics.com/careers/us/en/job/8003715?gh_jid=8003715","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-06-15T18:38:06Z","expires_at":"2026-08-15T14:19:58.709718Z","created_at":"2026-06-28T14:18:02.748446Z","updated_at":"2026-07-16T14:19:58.847175Z","company_name":"Qualtrics","company_slug":"qualtrics","company_logo_url":"https://www.google.com/s2/favicons?domain=qualtrics.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/55801a80-235c-4509-bc5c-551db3ccac1d"}],"market_demand_pack":{"amount_cents":2900,"api_checkout_url":"https://aidevboard.com/api/v1/checkout?product_id=aidevboard_ai_skills_demand_pack","checkout_url":"https://aidevboard.com/market-demand-pack?qc=api-jobs-market-demand-pack\u0026utm_campaign=skills_demand_pack\u0026utm_medium=jobs_api\u0026utm_source=api","currency":"USD","description":"Full ranked public AI/ML demand CSV, source job URLs, and decision brief with market and offer angles.","fulfillment":"automatic_email_after_paid_checkout","human_checkout_url":"https://aidevboard.com/market-demand-pack?qc=api-jobs-market-demand-pack\u0026utm_campaign=skills_demand_pack\u0026utm_medium=jobs_api\u0026utm_source=api","name":"AI Market Demand Pack","next_step":"Open checkout_url for Stripe Checkout, or call api_checkout_url to get the non-charging checkout handoff payload.","price_usd":29,"product_id":"aidevboard_ai_skills_demand_pack","quote_url":"https://aidevboard.com/api/v1/quote?product_id=aidevboard_ai_skills_demand_pack"},"page":1,"per_page":20,"total":390,"total_pages":20}